| Railway track fastener defect detection based on image processing and deep learning techniques: A comparative study X Wei, Z Yang, Y Liu, D Wei, L Jia, Y Li Engineering Applications of Artificial Intelligence 80, 66-81, 2019 | 272 | 2019 |
| Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques X Wei, M Verhaegen, T van Engelen International Journal of Adaptive Control and Signal Processing 24 (8), 687-707, 2010 | 178 | 2010 |
| Gain Scheduled Control for Air Path Systems of Diesel Engines Using LPV Techniques X Wei, L Del Re IEEE transactions on control systems technology 15 (3), 406-415, 2007 | 168 | 2007 |
| Multi-target defect identification for railway track line based on image processing and improved YOLOv3 model X Wei, D Wei, D Suo, L Jia, Y Li IEEE Access 8, 61973-61988, 2020 | 112 | 2020 |
| Sensor fault diagnosis of wind turbines for fault tolerant X Wei, M Verhaegen, T Van den Engelen IFAC Proceedings Volumes 41 (2), 3222-3227, 2008 | 102 | 2008 |
| Defect detection of pantograph slide based on deep learning and image processing technology X Wei, S Jiang, Y Li, C Li, L Jia, Y Li IEEE Transactions on Intelligent Transportation Systems 21 (3), 947-958, 2019 | 99 | 2019 |
| Self-powered triboelectric nano vibration accelerometer based wireless sensor system for railway state health monitoring X Zhao, G Wei, X Li, Y Qin, D Xu, W Tang, H Yin, X Wei, L Jia Nano Energy 34, 549-555, 2017 | 98 | 2017 |
| Urban rail track condition monitoring based on in-service vehicle acceleration measurements X Wei, F Liu, L Jia Measurement 80, 217-228, 2016 | 87 | 2016 |
| A comparative study on fault detection methods of rail vehicle suspension systems based on acceleration measurements X Wei, L Jia, H Liu Vehicle System Dynamics 51 (5), 700-720, 2013 | 78 | 2013 |
| LMI solutions to the mixed ℋ︁−/ℋ︁∞ fault detection observer design for linear parameter‐varying systems X Wei, M Verhaegen International Journal of Adaptive Control and Signal Processing 25 (2), 114-136, 2011 | 62 | 2011 |
| Sparse classification based on dictionary learning for planet bearing fault identification C Zhao, Z Feng, X Wei, Y Qin Expert Systems with Applications 108, 233-245, 2018 | 57 | 2018 |
| Sensor and actuator fault diagnosis for wind turbine systems by using robust observer and filter X Wei, M Verhaegen Wind Energy 14 (4), 491-516, 2011 | 55 | 2011 |
| Fault detection of large scale wind turbine systems: A mixed H∞/H−index observer approach X Wei, M Verhaegen 2008 16th Mediterranean Conference on Control and Automation, 1675-1680, 2008 | 50* | 2008 |
| A semi-active control suspension system for railway vehicles with magnetorheological fluid dampers X Wei, M Zhu, L Jia Vehicle System Dynamics 54 (7), 982-1003, 2016 | 48 | 2016 |
| Wear analysis and prediction of rigid catenary contact wire and pantograph strip for railway system XK Wei, HF Meng, JH He, LM Jia, ZG Li Wear 442, 203118, 2020 | 46 | 2020 |
| On fault isolation for rail vehicle suspension systems X Wei, L Jia, K Guo, S Wu Vehicle System Dynamics 52 (6), 847-873, 2014 | 44 | 2014 |
| On persistent excitation for parameter estimation of quasi-LPV systems and its application in modeling of diesel engine torque X Wei, L Del Re IFAC Proceedings Volumes 39 (1), 517-522, 2006 | 43 | 2006 |
| Robust fault detection observer design for linear uncertain systems X Wei, M Verhaegen International Journal of Control 84 (1), 197-215, 2011 | 40 | 2011 |
| Advanced LPV techniques for diesel engines X Wei na, 2006 | 39 | 2006 |
| Mixed H2212;/H∞fault detection observer design for LPV systems X Wei, M Verhaegen 2008 47th IEEE Conference on Decision and Control, 1073-1078, 2008 | 36 | 2008 |
Michel VerhaegenProfessor Systems and Control, Delft University of TechnologyVerified email at tudelft.nl
